Improved YOLO Pedestrian Detection Algorithm Based on Attention Mechanism

Author:

Yao Kun1,Shi Jiefu2,Xia Yu3

Affiliation:

1. Hohai University,Changzhou,China

2. Inner Mongolia Agricultural University,Baotou,China

3. Dalian University of Technology,Dalian,China

Publisher

IEEE

Reference12 articles.

1. ANALYSIS THE CLUSTER PERFORMANCE OF REAL DATASET USING SPSS TOOL WITH K-MEANS APPROACH VIA PCA

2. DPN-SENet:A self-attention mechanism neural network for detection and diagnosis of COVID-19 from chest x-ray images[J];r,2021

3. Real-Time Pedestrians Detection by YOLOv5

4. EBK-Means: A Clustering Technique based on Elbow Method and K-Means in WSN[J];bholowalia;International Journal of Computer Applications,2014

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Pedestrian tracking and counting based on YOLOv4 and DeepSORT in Subway Stations;2023 35th Chinese Control and Decision Conference (CCDC);2023-05-20

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